Expanding Capacity on a Nutanix environment – Design Decisions

I recently saw an article about design decisions around expanding capacity for a HCI platform which went through the various considerations and made some recommendations on how to proceed in different situations.

While reading the article, it really made me think how much simpler this process is with Nutanix and how these types of areas are commonly overlooked when choosing a platform.

Let’s start with a few basics:

The Nutanix Acropolis Distributed Storage Fabric (ADSF) is made up of all the drives (SSD/SAS/SATA etc) in all nodes in the cluster. Data is written locally where the VM performing the write resides and replica’s are distributed based on numerous factors throughout the cluster. i.e.: No Pairing, HA pairs, preferred nodes etc.

In the event of a drive failure, regardless of what drive (SSD,SAS,SATA) fails, only that drive is impacted, not a disk group or RAID pack.

This is key as it limited the impact of the failure.

It is importaint to note, ADSF does not store large objects nor does the file system require tuning to stripe data across multiple drives/nodes. ADSF by default distributes the data (at a 1MB granularity) in the most efficient manner throughout the cluster while maintaining the hottest data locally to ensure the lowest overheads and highest performance read I/O.

Let’s go through a few scenarios, which apply to both All Flash and Hybrid environments.

  1. Expanding capacityWhen adding a node or nodes to an existing cluster, without moving any VMs, changing any configuration or making any design decisions, ADSF will proactively send replicas from write I/O to all nodes within the cluster, therefore improving performance while reactively performing disk balancing where a significant imbalance exists within a cluster.

    This might sound odd but with other HCI products new nodes are not used unless you change the stripe configuration or create new objects e.g.: VMDKs which means you can have lots of spare capacity in your cluster, but still experience an out of space condition.

    This is a great example of why ADSF has a major advantage especially when considering environments with large IO and/or capacity requirements.

    The node addition process only requires the administrator to enter the IP addresses and its basically a one click, capacity is available immediately and there is no mass movement of data. There is also no need to move data off and recreate disk groups or similar as these legacy concepts & complexities do not exist in ADSF.

    Nutanix is also the only platform to allow expanding of capacity via Storage Only nodes and supports VMs which have larger capacity requirements than a single node can provide. Both are supported out of the box with zero configuration required.

    Interestingly, adding storage only nodes also increases performance, resiliency for the entire cluster as well as the management stack including PRISM.

  2. Impact & implications to data reduction of adding new nodesWith ADSF, there are no considerations or implications. Data reduction is truely global throughout the cluster and regardless of hypervisor or if you’re adding Compute+Storage or Storage Only nodes, the benefits particularly of deduplication continue to benefit the environment.

    The net effect of adding more nodes is better performance, higher resiliency, faster rebuilds from drive/node failures and again with global deduplication, a higher chance of duplicate data being found and not stored unnecessarily on physical storage resulting in a better deduplication ratio.

    No matter what size node/s are added & no matter what Hypervisor, the benefits from data reduction features such as deduplication and compression work at a global level.

    What about Erasure Coding? Nutanix EC-X creates the most efficient stripe based on the cluster size, so if you start with a small 4 node cluster your stripe would be 2+1 and if you expand the cluster to 5 nodes, the stripe will automatically become 3+1 and if you expand further to 6 nodes or more, the stripe will become 4+1 which is currently the largest stripe supported.

  3. Drive FailuresIn the event of a drive failure (SSD/SAS or SATA) as mentioned earlier, only that drive is impacted. Therefore to restore resiliency, only the data on that drive needs to be repaired as opposed to something like an entire disk group being marked as offline.

    It’s crazy to think a single commodity drive failure in a HCI product could bring down an entire group of drives, causing a significant impact to the environment.

    With Nutanix, a rebuild is performed in a distributed manner throughout all nodes in the cluster, so the larger the cluster, the lower the per node impact and the faster the configured resiliency factor is restored to a fully resilient state.

At this point you’re probably asking, Are there any decisions to make?

When adding any node, compute+storage or storage only, ensure you consider what the impact of a failure of that node will be.

For example, if you add one 15TB storage only node to a cluster of nodes which are only 2TB usable, then you would need to ensure 15TB of available space to allow the cluster to fully self heal from the loss of the 15TB node. As such, I recommend ensuring your N+1 (or N+2) node/s are equal to the size of the largest node in the cluster from both a capacity, performance and CPU/RAM perspective.

So if your biggest node is an NX-8150 with 44c / 512GB RAM and 20TB usable, you should have an N+1 node of the same size to cover the worst case failure scenario of an NX-8150 failing OR have the equivalent available resources available within the cluster.

By following this one, simple rule, your cluster will always be able to fully self heal in the event of a failure and VMs will failover and be able to perform at comparable levels to before the failure.

Simple as that! No RAID, Disk group, deduplication, compression, failure, or rebuild considerations to worry about.


The above are just a few examples of the advantages the Nutanix ADSF provides compared to other HCI products. The operational and architectural complexity of other products can lead to additional risk, inefficient use of infrastructure, misconfiguration and ultimately an environment which does not deliver the business outcome it was originally design to.

Erasure Coding Overheads – Part 1

Erasure Coding has become a hot topic in the Hyperconverged Infrastructure (HCI) world since Nutanix announced its implementation (EC-X) in June 2015 at its inaugural user conference and VMware have followed up recently with support for EC in its 6.2 release for All-Flash deployments.

As this is a new concept to many in the industry there have been a lot of questions about how it works, what are the benefits and of course what are the trade offs.

In short, regardless of vendor Erasure Coding will allow data to be stored with tuneable levels of resiliency such as single parity (similar to RAID 5) and double parity (similar to RAID 6) which provides more usable capacity compared to replication which is more like RAID 1 with ~50% usable capacity of RAW.

Not dissimilar to RAID 5/6, Erasure coding implementations have increased write penalties compared to replication (RF2 for Nutanix or FTT1 VSAN) similar to RAID 1.

For example, the write penalties for RAID are as follows:

  • RAID 1 = 2
  • RAID 5 = 4
  • RAID 6 = 6

Similar write penalties are true for Erasure coding depending on each vendors specific implementation and stripe size (either dynamic/fixed).

I have written a number of posts about Nutanix specific implimentation, for those who are interested see the following deep dive post:

Nutanix – Erasure Coding (EC-X) Deep Dive

VMware has also released a post titled The Use Of Erasure Coding In VMware Virtual SAN 6.2 covering their implementation of Erasure Coding by .

The article is well written and I would like to highlight two quotes from the post which are applicable to any implementation of Erasure coding, including Nutanix EC-X and VSAN.

Quote #1

Erasure Coding does not come for free. It has a substantial overhead in operations per second (IOPS) and networking.

Quote #2

In conclusion, customers must evaluate their options based on their requirements and the use cases at hand. RAID-5/6 may be applicable for some workloads on All-Flash Virtual SAN clusters, especially when capacity efficiency is the top priority. Replication may be the better option, especially when performance is the top priority (IOPS and latency). As always, there is no such thing as one size fits all.

Pros of Erasure Coding:

  • Increased usable capacity of RAW storage compared to replication
  • Potential to increase the amount of data stored in SSD tier
  • Lower cost/GB
  • Nutanix EC-X Implementation places parity on capacity tier to increase the effective SSD tier size

Cons of Erasure Coding:

  • Higher write overheads
  • Higher impact (read) in the event of drive/node failure
  • Performance will suffer significantly for I/O patterns with high percentage of overwrites
  • Increased computational overheads

Recommended Workloads to use Erasure Coding:

  • Write Once Read Many (WORM) workloads are the ideal candidate for Erasure Coding
  • Backups
  • Archives
  • File Servers
  • Log Servers
  • Email (depending on usage)

As many of the strong use cases for Erasure coding are workloads not requiring high IO, using Erasure Coding across both performance and capacity tiers can provide significant advantages.

Workloads not ideal for Erasure Coding:

  • Anything Write / Overwrite Intensive
  • VDI

This is due to VDI typically being very write intensive which would increase the overheads on the software defined storage. VDI is also typically not capacity intensive thanks to intelligent cloning so EC advantages would be minimal.


Regardless of vendor, all Erasure Coding implementations have higher overheads than traditional replication such as Nutanix RF2/RF3 and VSANs FTT1/2.

The overheads will vary depending on:

  • The configured parity level
  • The stripe size (which may vary between vendors)
  • The I/O profile, the more write intensive the higher the overheads
  • If the striping is performed in-line on all data or post process on write cold data
  • If the stripe is degraded or not from a drive/node failure

The usable capacity also varies depending on:

  • The number of nodes in a cluster which can limit the stripe size (see the next point)
  • The stripe size (dependant on number of nodes in the cluster)
    • E.g.: A 3+1 will give usable capacity up to 75% and a 4+1 will give up to 80% usable capacity.

It is importaint to understand as the stripe size increases, the resulting usable capacity increases diminish. As the stripe size increases, so do the overheads on the storage controllers and network. The impact during a failure is also increased as is the risk of a drive or node failure impacting the stripe.

In Part 2, I am planning on publishing testing examples to show the performance delta between typical replication and erasure coding for a write intensive workload.

Related Articles:

  1. Large scale clusters and increased resiliency with RF3 + EC-X
  2. What I/O will Nutanix Erasure coding (EC-X) take effect on?
  3. Sizing assumptions for solutions with Erasure Coding (EC-X)

Heterogeneous Nutanix Clusters Advantages & Considerations

Lets start with a simple example, the below shows a 4 node cluster mixing 2 x NX-3060 nodes with 2 x NX-8035 nodes. Both node types share the same Haswell CPU types but the NX-3060 has ~2TB usable and the NX-8035 has ~8TB usable.


Assuming the cluster capacity was 50% utilized the NDSF layer would look similar to this:


The above shows the NDSF having a total Storage Pool capacity of 20TB with 50% used (10TB). As we have a heterogenous cluster, we have 2 different node types with vastly different usable capacity.

Nutanix Disk Balancing automatically balances the storage to ensure the utilization percentage of all SSDs/HDDs within the cluster are within +-15%. This means administrators do not have to worry about capacity management on a per node basis, capacity management only needs to be performed at the storage pool (cluster) layer.

Advantage 1: No silos of storage capacity is heterogeneous environments

Advantage 2: NDSF disk balancing ensures the data is evenly distributed throughout the cluster

Advantage 3: There is no requirement for hypervisor level storage capacity management such as Storage DRS (SDRS).

For more information on why Storage DRS is not required see: Storage DRS and Nutanix – To use, or not to use, that is the question?

In a heterogeneous environment, it is likely you will have multiple workloads with different capacity and performance requirements. The below diagram shows the same 4 node cluster, with a single storage pool and 4 containers with different data protection and reduction settings to suit a wide range of application requirements.

Note: The RF3 container shown below would only be possible in clusters of 5 nodes or more, but is shown to illustrate the flexibility/capabilities of NDSF.


The storage pool itself has up to 20TB usable (assuming RF2 and excluding data reduction savings). In the Pool we can see four Containers which can be thought of as policies which can be applied to Virtual Machines or Virtual Disks.

Container01 is configured with RF2 and In-Line compression and reports 10TB free space as the underlying storage pool (where capacity is managed) is 50% utilised. Therefore the Container reports free space as all the available capacity within the Storage Pool based on its configured RF.

Container02 has RF2, In-Line compression and EC-X enabled but you will note it also reports 10Tb free space, as capacity is not assigned to a container, its shared between all containers within a Storage Pool.

Container03 is configured with a RF3 which is different to Containers 01 and 02, as such the container reports free space based on its configured RF of 3, so it shows 13.3TB usable and 6.66Tb free space as that is the maximum data that can be supported in that container based on its storage policies.

Container04 reports the same free space as Container 01 and 02, as its configured with the same RF. While Container04 has all data reduction technologies enabled, the Container reports actual free space, as data reduction takes effect the usable capacity will change.

It is possible to set capacity reservations on Containers where an application or tenant requires a guarantee as to the usable capacity available, it is also possible to set limits on containers to prevent workloads using more than a specified amount of capacity. However, for most use cases, I recommend not using Reservations or Limits and simply manage capacity at the Storage Pool layer.

Nutanix also supports VMs with more assigned/used capacity than the node they are running on, for more information see: What if my VMs storage exceeds the capacity of a Nutanix node?

Regardless of what node type/s reside within a Nutanix cluster, there is no advanced settings required to be configured such as Queue Depths, VAAI and multi-pathing, which can be required when mixing legacy storage platforms in the same cluster. There is also no requirement for Storage DRS to manage either performance or capacity as discussed earlier.

Advantage 3: No silos of storage capacity, all capacity is shared in the storage pool

Advantage 4: Storage policies such as RF and Data Reduction can be changed on the fly as required and multiple policies are supported within the same cluster.

For more information about Nutanix data reduction technologies, see: Nutanix Implementation of Data Avoidance & Reduction Technologies

Regardless of the mixture of node types and their respective capacity/performance characteristics, there is no advanced configuration required to achieve optimal performance.

Nutanix automatically manages I/O pathing and as data locality ensures most data is read locally and writes are always written local to the VM and then replicas distributed throughout the cluster, it minimizes the chances of hot spots by default.

In the unlikely event one nodes local SSD tier becomes saturated, NDSF will automatically write data across the shared SSD tier until the local nodes SSD tier has sufficient capacity to resume local writes. This avoids the requirement for a storage admin to take any corrective actions.

Advantage 5: In the unlikely event of saturation of a nodes SSD tier, NDSF automatically redirects new I/O until ILM (tiering) can free up capacity within the local tier.

NDSF natively distributes writes throughout all nodes within the cluster. This means all nodes within heterogeneous clusters increase the capacity, performance and resiliency of the entire cluster.

To increase the performance of a single VM, you have numerous options. All you need to do is migrate (vMotion for ESXi, Live Migration for Hyper-V or Migrate for AHV) to a node with higher spec physical processors, more SSD drives and/or more SATA spindles.

There is no requirement to Storage vMotion, or relocate the VM to a new Datastore/Container. NDSF manages the storage layer automatically and will localize hot data if/when required.

Advantage 6: No silos of storage capacity, all capacity is shared in the storage pool

Advantage 7: All nodes contribute to the capacity, performance and resiliency of the cluster

Heterogeneous clusters are managed by a single HTML 5 GUI called PRISM. There is no need to access multiple management interfaces for different storage types.

Advantage 8: Heterogeneous clusters are managed via a single HTML 5 GUI.

Nutanix also supports Pin to SSD which allows workloads requiring all flash to reside within a hybrid (SSD+SATA) cluster and be guaranteed all flash performance.

VMs or Virtual Disks can also be marked to be stored solely in Flash on the fly if/when required and vice versa.

Advantage 9: No silos required for workloads requiring All Flash performance

Nutanix eliminates the complexity around managing performance at a datastore layer. Nutanix supports up to the chosen hypervisors limits, e.g.: vSphere HA limit is 2048 VMs per datastore. As all controllers within a cluster actively service all datastores (Containers), performance isn’t constrained at a datastore layer like with traditional storage products.

For more information see: Unlimited VMs per datastore? Its not a myth with Nutanix!

Advantage 10: No performance concerns/constraints at the datastore level

What about Considerations for Heterogeneous Clusters?

From a performance perspective, always ensure you size to have your N+x (e.g.: N+1 , N+2 etc) node/s sized >= the largest node in the cluster to ensure in the event of a node failure, workloads benefiting from higher performance nodes can failover to equivalent nodes.

From a capacity perspective, for NDSF to be able to restore the configured RF (RF2 or RF3) in the event of a node failure, sufficient capacity must exist within the storage pool. As such, when using high capacity nodes such as NX-8035s , NX-8150s or NX-6035C storage only nodes, ensure you have >= capacity of the largest node free within the storage pool.

Advantage 11: Performance and availability sizing for heterogeneous clusters is simple.

Another consideration is for mission-critical or high I/O applications, spread these evenly across the nodes and ideally ensure the active working set fits within the local SSD tier. Doing so will maximise performance, but in the event a very large workload cannot fit with the local SSD, its data will resided within the shared SSD tier and be actively serviced by multiple Controller VMs.

For more information about sizing see:  Rule of Thumb: Sizing for Storage Performance in the new world.

Advantage 12: The NDSF shared SSD tier ensures in the event a workload exceeds the local SSD capacity that the application still enjoys all flash performance by distributing data intelligently across the cluster.

Over time, when adding new nodes, VMs can be quickly/easily migrated to newer, higher performance/capacity nodes without any preparation. The VMs will immediately benefit from the newer nodes CPU,RAM and storage performance even if most of its data is still stored on older node types.

Older nodes can be non disruptively removed once they are end of life, again without any preparation or administrator intevenston.

Advantage 13: Workloads on NDSF benefit from newer generation nodes immediately without complex design/migration activities.


  • Nutanix supports and recommends heterogeneous clusters
  • No complexity with multi-pathing, it’s optimal out of the box
  • No custom per datastore configuration
  • VAAI just works, no advanced configuration required due to mixed node types
  • No compromise required to mix node types
  • No silos of storage capacity, all capacity is shared in the storage pool
  • All nodes contribute to performance of the cluster
  • No balancing VMs across datastores/storage devices is required to improve performance/resiliency
  • NDSF disk balancing ensures the data is evenly distributed throughout the cluster helping avoid hotspots
  • The distribution of RF traffic throughout the cluster also helps avoid hotspots
  • No silos required for workloads requiring all flash performance
  • NDSF ensures VMs can immediately benefit from the addition of newer generation node types
  • Nodes can be added/removed without system administrator performing data migrations